Possibilities for the integration of fish farming into irrigation systems
Bibliographic record
Abstract
Harvesting fish in irrigation systems, sometimes involving some form of husbandry or even culture, is a practice which dates back at least two millennia. Although seldom recorded, it seems to have been widespread in the tropics and subtropics, especially in rice fields. In the present century, improved management for land‐based crops and the demands for the successful raising of aquatic organisms were not generally compatible, but with the advent of integrated crop protection, this situation has changed drastically. Moreover, irrigation systems using stored or diverted water have increased exponentially during the past 50 years, but fish farming within these irrigated systems has not expanded equally, and therefore, there is now a huge potential for this integrated enterprise. A systematic approach to fish farming development at irrigation system level which will make this integration a viable enterprise is proposed. The whole range of aquatic habitats created by irrigation systems can be integrated with fish farming. Small and large irrigation reservoirs, the extensive network of irrigation canals, the irrigated fields themselves, as well as adjacent ponds or aquatic refuges of various sorts are all potential sites for nursing or grow‐out of fish. In many countries, there is now relatively easy access to fish seed, even in inland areas. Permanent water bodies should be stocked with a central pool of culture species harvested from short‐lived habitats which serve as nurseries. A flexible system of moving culture fish within the system of habitats should be feasible. For example, stocking material for reservoirs can be obtained from irrigated rice fields where the short maturation period of the crop only permits the harvest of fingerlings. If a pragmatic and flexible approach is made to use all habitats for fish production, there could be a year‐round supply of fish and a minimum wastage of stocks of cultured fish. The use of high‐yielding fish of good quality is essential for economic viability. In areas where a high diversity of fish with a requisite biomass of desirable species already exists, these indigenous fish can be harvested, but their yields may only be adequate for low‐income rural areas. Common carp, Cyprinus carpio L., has traditionally been a preferred cultured species. Tilapia are proposed as an alternative because these fish are cheap to raise, give high yields and are also quite palatable. Aside from economic revenues, this type of integration also involves ecological and social benefits. High densities of fish in irrigation systems enhance the yield of land crops, alleviate the pressure of terrestrial and aquatic pests, and lower the populations of vectors of diseases of man and domestic animals.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.014 | 0.003 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".